1. Technical Field
The present invention relates generally to an apparatus and method for monitoring the abnormal state of a vehicle using a clustering technique. More particularly, the present invention relates to an apparatus and method for monitoring the abnormal state of a vehicle by applying a clustering technique to data collected from an electronic control unit mounted on a vehicle that is running.
2. Description of the Related Art
A vehicle is a very complicated and delicate machine composed of tens of thousands of mechanical parts and has changed from being a mechanical device into being an electronic device due to the introduction of electronic components. In particular, vehicles have been developed into safer and more efficient means of transportation as a result of such changes.
An electronic control system, such as an Electronic Control Unit (ECU), has been introduced to vehicles that have recently been produced, and pieces of data about individual detailed devices based on the engine of a vehicle are measured through such an electronic control system. The pieces of measured data not only can be used for the electronic control of the vehicle, but also can be collected, analyzed and managed by a server that manages the vehicle using communication technology. Information about each vehicle may enable efficient vehicle maintenance to be performed through continuous management, and may be applied to detailed fields related to vehicle driving, such as automobile insurance, logistics, traffic, and environments. Further, when an abnormality occurs in a vehicle, the state of the vehicle can be remotely diagnosed based on the information about the vehicle, and action can be taken in certain situations to promptly cope with a given situation, thus improving the safety of the vehicle and reducing a loss of lives caused by accidents.
However, technology for monitoring the state of a vehicle through the analysis of the Control Area Network (CAN) data of the vehicle is limitedly applied only to a specific device of a vehicle at the present time, as disclosed in Korean Unexamined Patent Publication No. 10-2004-0033454 (entitled “System and method for predicting the turning-off of an engine”). For example, the application of technology is limited only to some devices, such as for the lifespan of a battery or a vehicle, and technology for monitoring the state of the vehicle in response to complex factors of several devices using the CAN data of the vehicle at a remote server is insufficient.
For example, methods of monitoring or diagnosing the state of a vehicle presented in a vehicle maintenance system function to continuously observe vehicle data, such as the travel distance, oil pressure over time, and battery voltage of each vehicle, monitor the state of the vehicle which is approaching a time point (threshold) at which the abnormal state of the corresponding device statistically occurs, and notify a vehicle driver or a vehicle management system of the monitored state. FIG. 1 is a graph applied to a method in which a module for diagnosing the state of a vehicle monitors the state of a battery voltage. Referring to FIG. 1, ‘A’ denotes an area indicative of a state which the battery voltage is approaching that of a time point ‘B’ at which an abnormality statistically occurs in the battery while the module for diagnosing the state of the vehicle is continuously observing the battery voltage.
Further, in the case of methods of predicting the lifespan of a vehicle, there has been proposed a method of estimating a daily average mileage of the vehicle and predicting a vehicle lifespan inversely proportional to the daily average mileage. Such a prediction method is a simple method used to predict an abnormality in the specific device of a vehicle or predict the lifespan of parts or devices, and is problematic in that it is impossible to monitor an abnormal state occurring due to complex factors and correlations between a plurality of devices constituting the vehicle. In order to solve this problem, normalization is required in which pieces of data about respective devices having different thresholds are considered, and technology for applying correlations to a monitoring and diagnostic model is also required.